Technology

VP of Corporate Strategy at Warner Bros. Discovery, Bisaria will contribute her extensive experience in corporate strategy and innovation to the company’s board.

KoobrikLabs, a leading AI partner for the creative industries, today announced the appointment of Shilpa Bisaria, Vice President of Global Corporate Strategy at Warner Bros. Discovery (WBD), to its Board. 

Bisaria brings more than 15 years of global experience in growth strategy, innovation, and business operations, with a career spanning emerging technologies, media, content distribution, and strategic development across complex, high-growth organizations. Her expertise strengthens KoobrikLabs’ mission to build intelligent systems and creative tools that redefine how people work, create, and communicate. 

“Shilpa is an exceptional strategic thinker and a visionary leader at the forefront of the convergence between technology and storytelling, She’s been a real champion of ours as the leader of the Warner Bros Innovate on the Lot accelerator and her strategic thinking about how new tools can transform creative corporations is invaluable to our growth as we build these tools at KoobrikLabs.” 

Orlando Wood, CEO of KoobrikLabs.

In her current role at Warner Bros. Discovery, Bisaria leads high-impact, cross-functional initiatives across strategic planning, content optimization, and innovation. In the year Warner Bros. celebrated its 100th anniversary, she conceptualized and launched Innovate On The Lot, WBD’s emerging-technology accelerator designed to shape the next century of storytelling innovation, of which Koobrik and KoobrikLabs are alumni.  

Prior to joining WBD’s Global Corporate Strategy team, Bisaria held leadership roles across WarnerMedia Sales & Distribution – including Content Licensing, Home Entertainment, Advertising Sales, and Distribution – and previously served as an engagement manager at Innosight, the strategy consulting firm. 

“I’m excited to join KoobrikLabs at such a pivotal moment in the evolution of technology in the entertainment industry, The team is building transformative technology that empowers creative companies. We’ve found them to be the right blend of tech-forward while being artist first. I look forward to contributing to KoobrikLabs’ strategic direction as we navigate the next evolution of innovation.” 

Shilpa Bisaria, Board Member of KoobrikLabs

Bisaria’s appointment further strengthens KoobrikLabs’ commitment to combining cutting-edge technology capability with creative industry expertise, to deliver solutions that enhance human creativity, efficiency, and decision-making. 

Shilpa joins existing board members including famed film producer and ex-Chairman of Sony Pictures, Jon Peters and Chief Scientist (Neural Networks) at Databricks, Dr Jonathan Frankel. 

About KoobrikLabs 

KoobrikLabs builds intelligent AI, data and cloud solutions that elevate creativity and empower individuals and organizations to bring their ideas to life. By building and supporting human-centered technology, KoobrikLabs helps creative teams to move faster, safer, and smarter.

This month felt like AI moved into the machinery.

Government. Defense. Hiring. Advertising. Startup funding. Data infrastructure. Diplomacy. Speech. Cybersecurity. Football ads, somehow.

All the normal places.

Compute became currency

OpenAI offering Y Combinator startups up to $2M in API credits in exchange for equity was one of the cleanest tells of the month.

Sam Altman has worked out how to invest using his own fuel. Not cash. Compute.

In 2026, that might be close enough.

For OpenAI, it is brilliant. Equity upside, distribution, dependency, and a front-row seat to the next generation of companies being built.

For startups, it is tempting too. $2M in credits is real money when your product is basically a nice interface and a terrifying token bill.

The platforms are getting closer to the cap table.

Which feels important.

Also faintly medieval.

YC quietly changed the startup religion

Y Combinator also put out its latest Requests for Startups, and the really interesting bit was the push toward AI-native service companies.

For years, the religion was SaaS. High margin. Low touch. No messy humans.

Now YC is basically asking: what if AI lets service businesses scale like software?

Quiet announcement. Big signal.

The services layer may be where a lot of the real value lives. Which is funny, because the pitch was that AI would do everything.

Turns out “doing everything” might itself be a service business.

Advertising got a new payment model

JLR hiring WPP on an outcome-based remuneration model feels like a big one for advertising.

Agencies have talked about moving away from hours forever. Somewhere, a strategy director in 1998 is still saying “we should be paid for value, not time” while making a deck about brand love.

Now JLR and WPP are actually doing it.

If machines do more of the execution, clients are going to care less about how many people touched the work and more about what actually happened.

Did sales move?

Did demand grow?

Did the brand get stronger?

Did the work do the thing?

Terrifying for the old agency model. Quite exciting for people who can actually deliver.

And the holding companies seem to know it.

Publicis bought LiveRamp for $2.2B, which is basically a giant bet that in the AI marketing era, the cleanest data pipes build the smartest systems.

Less “who has the best deck.”

More “who has the best data.”

Slightly less romantic. Probably more valuable.

The labs moved into implementation

Anthropic’s enterprise services venture acquiring Fractional AI, hot on the heels of OpenAI launching its Deployment Company and buying Tomoro, felt like another big tell.

For a while, the labs said: here is the model.

Now they are saying: here is the model, the implementation team, the workflow playbook, the engineers, the platform, and eventually, presumably, the invoice for your entire operating model.

They are coming for everything.

Quietly at first.

Then all at once.

The market found religion in data centers

The Dow hit all-time highs again this month, helped along by AI optimism, chip stocks, and the market’s continuing belief that if we simply build enough data centers, everything will probably be fine.

Very comforting.

Nothing says “healthy economy” like looking under the hood and finding Nvidia, Micron, hyperscaler capex, and a cooling bill the size of a mid-tier nation.

The economy is three data centers in a trench coat remains one of the more accurate things I have said recently.

I’m sure the trench coat is structurally sound.

Context windows got silly

Subquadratic came out with SubQ, claiming a 12 million-token context window and an architecture that makes long-context analysis dramatically cheaper.

If true, that is a big deal.

Whole codebases.

Whole legal archives.

Whole financial histories.

Finally, an AI that can read the entire mess instead of asking you to upload it in sad little chunks.

Psst… 12 million tokens.

China credentialed the influencer economy

China tightened rules around influencers giving advice on finance, health, law and education, requiring verified qualifications before people can cosplay as experts online.

On one hand, fewer fake finance gurus in rented Lamborghinis feels like a civilizational win.

On the other hand, giving the state a big “qualified to speak” stamp has… range.

Still, if this prevents one more 23-year-old from explaining passive income in front of a rented Lamborghini, civilization gets a small point on the board.

AI got a government badge

This month, AI also marched into the machinery of civilization wearing a suit that didn’t quite fit.

The Pentagon reportedly signed classified AI agreements with major tech companies, while Anthropic was left outside the room because it would not loosen restrictions around surveillance and autonomous weapons.

Anthropic spends all this time trying to be the sensible one, and the reward is apparently being told it can’t come to the really serious meetings where sensible people might have been useful.

I honestly don’t know what to feel.

Proud of Anthropic.

Safer.

Also somehow less safe.

Since Nagasaki, humans have done the one thing that makes us the most human: agreed to stop using a technology that could destroy us all.

Will the AIs be so human?

OpenAI also got FedRAMP Moderate authorization, meaning U.S. government agencies can more easily use ChatGPT Enterprise and its API platform.

So ChatGPT has a government badge now.

I assume it will soon be attending a mandatory compliance webinar and eating a depressing sandwich under fluorescent lights.

AI started interviewing people

Amazon rolled out agentic software for hiring and supply chains, including AI-led interviews and recruiter notes.

I understand the appeal. Hiring is slow. Supply chains are complicated. Humans are expensive and occasionally want chairs.

But there is something very modern about being assessed for “culture fit” by a machine that has never once endured a company offsite.

The future of work is getting very efficient.

Possibly too efficient.

The CEOs went to China

Trump’s trip to China was one of the biggest stories of the month.

The interesting bit was who followed him there.

America’s most powerful CEOs were in Beijing meeting Chinese regulators and ministers around market access, regulatory barriers and deals.

And I know this is how business has always worked to some extent. But the mask feels thinner now.

We used to pretend these trips were about diplomacy, with business somewhere politely downstream of the statecraft. This felt more like the CEOs were the delegation, and the diplomats were doing continuity paperwork in the background.

China, I’m quite sure, had its diplomats on the other side. People who have spent lifetimes learning how to think in decades.

Meanwhile, democracies keep changing leadership every few years, and the tech elite just keep compounding.

There’s that line in Succession where Logan says: “I’ve been president. Lot longer than he has.”

No idea why that came to mind.

Adidas saved the mood

And then, thank God, Adidas released Backyard Legends.

A proper big football ad.

Starry. Silly. Majestic. World Cup energy.

Messi, Bellingham, Beckham, Zidane, Lamine Yamal, Trinity Rodman, Bad Bunny, and somehow even Timothée Chalamet works.

It reminded me of those old World Cup ads like The Other Game and Good vs Evil, where advertising remembered it was allowed to be grand, funny and slightly ridiculous.

Honestly, it felt right.

A useful reminder that amid all the capital allocation, compute deals, defense contracts, and machine-led interviews, creativity can still just make the room feel better.

And then, Milla Jovovich gave us the cherry on the cake!

My random inclusion that makes me unexpectedly happy: Milla Jovovich of The Fifth Element fame released an open-source AI memory tool based on the ancient Greek memory palace technique.

Sci-fi.

Models.

Ancient Greek memory theory.

So yes, it ticks all my boxes.

In a month full of compute-for-equity deals, government badges, AI hacking, machine-led interviews and CEOs doing diplomacy, there was something genuinely delightful about Leeloo helping improve RAG.

Honestly, fair enough.

And I’d revise the final section like this:

So what was the month?

Compute became startup currency.

YC rediscovered services.

Agencies moved toward outcomes.

Holding companies bought data pipes.

Labs moved into implementation.

Markets found comfort in data centers.

Context windows got ridiculous.

China credentialed the influencer economy.

AI got a government badge.

Hiring got more automated.

CEOs became diplomats.

AI hacking became industrial.

Adidas remembered how to make a football ad feel like an event.

And Milla Jovovich somehow wandered in with ancient Greek memory theory.

The connective tissue is pretty clear.

AI is changing how work gets sold, bought, funded, staffed, measured and paid for.

It is also changing who gets a seat at the table.

And this month, apparently, the answer was: the platforms, the labs, the CEOs, the holding companies, the governments, the investors, and Leeloo with a memory palace.

This month felt like the moment AI became something you can hand work to, leave running, and check back on later.

Agents got more practical.  The labs shipped faster.  Enterprise became the main battlefield.  Media companies kept consolidating.  Labor pressure kept showing up in increasingly polite language.  Defense moved closer to the center.  And every week seemed to arrive with at least one sentence that would have sounded completely unhinged six months ago and now just lands as normal industry news.

So, yes.  Quite a month.

A few weeks ago, OpenClaw gave people a glimpse of what it looks like when an agent can take over your computer and actually get on with things.  Then Claude Managed Agents arrived, and suddenly that same basic promise felt much closer to being usable by normal people and companies that enjoy things like permissions, security and not accidentally handing their laptop to a demon.

I now have tasks I hand Claude before I go to bed and routines it does before I get up.

That is useful.  It is also a slightly mad sentence to be able to write with a straight face.

Google had its own version with Agent Smith, an internal coding agent that can work in the background while employees check in from their phones.

OpenAI spent the month shipping like a company with something to prove… where the product velocity itself became the story.

They launched the best image model I’ve seen.  They dropped 5.5.  Codex kept pushing further into managed-agent territory.  Frontier gave them a cleaner enterprise story.  Astral strengthened the developer tooling story.  Jony Ive kept the hardware ambition alive.  Ads started looking like real revenue.  Sora got complicated.  The adult chatbot got shelved.

It was a lot.

The through-line feels pretty clear.  OpenAI is shaping itself around scale, revenue and durability.  If you are trying to justify a valuation that starts with a T, product sprawl starts to look expensive very quickly.

So the company spent the month looking more like a business preparing to make a very large argument to the market.

Anthropic had a very Anthropic month.

They continued to look like the adults in the room.  Claude Managed Agents felt careful, useful and closer to something a company could actually trust.  Their handling of Mythos, the powerful cyber model they appear to be holding back, also felt like them trying to lead from the front.

On the other hand… holy shit.

If a model is so capable that you are thinking about giving it to cybersecurity firms first so everyone can prepare, that is both responsible and wildly unsettling.

Then Claude Code had its wobble.  Anthropic admitted users had been having very different experiences over several weeks because of changes to reasoning defaults, caching and prompts.  Which means if you were building something over that period, the quality of your code could have been swinging around quite a lot.

Not ideal when your coworker is made of probability.

Then there was the Claude source code leak.  Human error, apparently.  No customer data exposed, apparently.  Still, when one of the most trusted companies in AI safety accidentally drops internal code into the wild, it does focus the mind a bit.

And Also, there was the research suggesting Claude has internal patterns that vaguely resemble stress and hesitation.

Which is comforting, I guess.

Even the machines seem a little overwhelmed.

Google launched everything, everywhere, all at once

Agent Smith.  Gemma running locally.  Gemini upgrades.  Deep research.  Enterprise agents.  More AI inside internal workflows.  More AI inside developer workflows.  More AI seemingly everywhere.

We use a lot of it in enterprise, and it is genuinely impressive.

As a consumer, though, I still find Google strangely hard to orient around.  OpenAI and Anthropic feel like they are building from a place I can understand.  Google has everything.

It is a bit like a Walmart.  You can get guns and candy bars, but where do you even begin?

That may sound flippant, but I think it matters.  Capability is one thing.  A clear place to start is another.

Google has the capability.  Possibly more capability than anyone.

The map is still a little… Googley.

This was also the month where the labor story got harder to avoid.

Indian factory workers are now being paid to film themselves doing everyday chores so AI systems can learn from them.  Lovely little reminder that the robot future still starts with humans teaching it how to wash a plate.

Oracle cuts.  Amazon cuts.  HSBC weighing major cuts.  Marvel and Disney finding cheaper structures.  Ben Affleck’s AI production company talking about creativity while the cost savings quietly did a lot of the selling.

The language around all of this is always elegant.  Efficiency.  Optimization.  Transformation.  Productivity.

The spreadsheet, as ever, is grinning quietly in the corner.

Marvel and Disney were an especially good example.  They are not exactly on the breadline.  They found a way to pay less.  And in America, where employing people comes with the world’s most expensive healthcare side quest, geography becomes part of the cost structure very quickly.

A studio decision becomes a labor story.
A labor story becomes a healthcare story.
A healthcare story becomes a geography story.

Everything rhymes if you stare at it long enough.

Also, the one-person company became less theoretical

The Medvi story really stuck with me.

For the last couple of years, “the one-person billion-dollar company” has sounded like something someone says on a podcast after drinking too much cold brew.

Then suddenly there it was.  One founder.  A stack of AI tools.  Serious revenue.

Now, of course, the details matter.  And “one-person company” is often cleaner as mythology than as operational truth.  But the broader point feels real.

A much smaller number of people can now do a much larger amount of work.

Exciting if you are the founder.

Slightly less relaxing if you are the department.

Defense and geopolitics moved closer to the center

The Palantir Maven story was one of the biggest of the month.

AI is now moving deeper into battlefield planning and execution.  Which is one of those sentences people will say very calmly on a panel before moving on to the next slide.

Then came the Iran girls’ school strike reporting, which raised serious questions around targeting data, decision-making and what happens when these systems are used in environments where mistakes are measured in lives.

Are we totally cool putting AI into weapons?

Are we cool with our enemies doing it?

Because that feels very much like a procurement question now.

And then the Carnegie piece on Iran, Korea, chips and energy tied it all together.  A regional conflict becomes an energy story.  The energy story becomes a semiconductor story.  The semiconductor story becomes an AI infrastructure story.

A few weeks ago I said everything is connected.  This was exactly what I meant.

The whole thing feels less like “tech” and more like the wiring diagram of modern life.

Media consolidation kept reminding everyone who has leverage

The Warner / Paramount story sat in the background of the month too.

The board approved the merger while thousands of artists signed a petition trying to block it.  A lot of the same type of people who were against the Netflix purchase seem very against this too.

Does it feel like rich, famous people just do not want things to change?

I wonder why that is.

Media consolidation, AI tooling, labor anxiety and distribution power are all part of the same weather system now.  The industry is changing shape, and everyone is trying to work out where they stand when the music stops.

Some people are worried about art.
Some people are worried about jobs.
Some people are worried about leverage.

Often, it is all three.

The Sam Altman question kept hanging over everything

The Ronan Farrow and Andrew Marantz piece on Sam Altman stayed with me because it put the human question back in the middle of the machine story.

It is easy to talk about models, benchmarks, product launches and valuations.  It is harder to sit with the fact that an enormous amount of power is concentrating around a very small number of people making very large decisions very quickly.

Sam Altman runs the biggest AI company in the world.

The question of whether he can be trusted is clearly not going away.

And honestly, it should not.

If this technology is going to sit underneath work, media, defense, commerce, education and daily life, then the character and incentives of the people steering it matter.

Quite a lot, actually.

Jensen had the line of the month

Jensen Huang saying he “thinks” we “might” have achieved AGI remains one of the more extraordinary moments of the month.

Pretty cuckoo thing to announce in that exact tone.

Like discovering fire and calling it a maybe.

Ok, uh… cool?  Maybe we should check?

And then, thank God, Milla Jovovich saved the vibe

My random inclusion that made me unexpectedly happy this month was Milla Jovovich of The Fifth Element fame releasing an open-source memory tool based on Greek memory palace techniques.

Sci-fi.
Models.
Ancient Greek memory theory.

So yes, it ticks all my boxes.

In a month full of trillion-dollar valuations, leaked code, defense AI, labor anxiety and markets pretending everything is fine, there was something genuinely delightful about Leeloo helping improve RAG.

Honestly, fair enough.

So what was the month?

Agents became practical.
OpenAI got sharper.
Anthropic looked responsible and terrifying.
Google launched half the universe.
Labor pressure became harder to dress up.
Defense got closer.
Media consolidated.
The money got louder.
The products got faster.

And the people building all of this kept shipping at a pace that feels too fast for anyone to fully understand, including, occasionally, themselves.

The connective tissue is pretty simple.

AI is moving into the operating layer of everything.

Work.
Code.
Media.
Defense.
Healthcare costs.
Supply chains.
Creative production.
Corporate restructuring.
The stock market’s increasingly cheerful belief that all of this is fine.
The S+P just closed at an all time high…

I don’t see how any of this could possibly go wrong.

Hannah Einbinder recently made a pretty incendiary comment about people using AI creatively. Her argument, in essence, was that these people are losers. Not artists. Not creative. People trying to rob real artists of their gifts.

Here’s the full quote:

“The people who make this stuff are losers.  They’re not artists.  They’re not creative.  And they’ve wanted their whole lives to be special.  And they’re not special.  They’re trying to rob creative people of our gifts.  And you can’t.  And even if you try, you will never be cool.  You guys suck.  No one likes you.  Anyone who’s near you is because they crave power and access over any ethical standard.  You are a loser.  You will never be cool.  And you probably had a rolly backpack in high school.  I wanna put your head in a toilet and flush.”

It is an incredibly sharp thing to say.  And she’s painting with such a broad brush, it’s almost hard to see who she’s talking about…. The CEO’s, the engineers, the users, or the creators…

But beneath the insult is a serious point.

A lot of these tools were trained on work taken without meaningful credit, consent, or compensation.  That matters.  It’ss not a trivial footnote.  It’s the central ethical complication in this whole conversation, and it is one of the reasons AI feels different from so many earlier technological shifts in art.

That part should not be hand-waved away.

But once you move from condemning the system to condemning every person using the tools, the argument starts to break down.

Because the question underneath all of this is an old one…  Who gets to call themselves an artist?

I grew up around one version of that question.

My mother was an ex-model, photographer, and author of nineteen books, many of them New York Times bestsellers.  She always looked down on people in advertising.  Her disappointment in me going into that world was only partially offset by her relief that I might actually be able to pay my rent.   The age old question of art vs. commerce arose, even then…

Her view was that people in advertising pretended to be artists but were not really artists because they were getting paychecks.  They were not making a living from their art, in her eyes.  They were making a living by persuading Coca-Cola to buy their art and then forcing people to watch it.

It was a harsh view, but it was coherent.  And she had lived by the sword of that creative risk so, much like Hannah Einbinder, she was entitled to her opinion.

And then, in one of life’s little jokes, she ended up dying as Lady Lowe…  I am still convinced this was, at least partly, my fault…. When they met at dinner she would have normally turned her back but for him confirming that “Weeden and whatever” was ACTUALLY a very good agency and I was not, in fact, wasting my life getting stoned in Amsterdam.  Well, I wasn’t wasting my life, at least.

But the point remains.  Her test for artistic legitimacy had a lot to do with sacrifice.  If someone was paid reliably, commissioned, sheltered by commerce, or buffered from risk, they became creatively suspect.

To her, art had to cost you something.  Security mostly.

And Hannah’s position, whether she means it this way or not, belongs to a very old tradition.  The tradition that says art must cost you something.  That if you are not willing to risk comfort, security, status, maybe even rent, then your commitment is suspect. That real artists stake their lives on the work.

There is something noble in that idea.  I won’t pretend otherwise.

A lot of extraordinary artists have done exactly that. They have lived precariously, chosen the work over stability, suffered for it, and made things the rest of us are lucky to inherit. There is real courage in betting on yourself that way. There is real dignity in it too.

I’ve spent my life idolizing creative people who have done just that.  Directors, Agency people who set up their own companies, even the freelance crew members who risk their mortgage on a security free engagement, trusting that their talent will lead to more work.

But suffering is not the same thing as legitimacy.

Being willing to suffer for your art may make you a crusader.  It may make you brave.  It does, in many cases, make the work better.  But it doesn’t automatically diminish the people who want some encouragement before they leap.  It doesn’t disqualify the people who want to grow in public.  It doesn’t make every person using accessible tools a fraud.

Some people need a little positive feedback before they are willing to risk their lives and their rent.

That doesn’t make them less human.  And I don’t think it makes them losers.

Creativity has always been full of these tests.

If someone pays you, are you still an artist?  If your work has a client, are you still an artist?  If your art is made inside a system of commerce, are you somehow less pure?  If a tool makes part of the process easier, are you less real?  If you did not suffer enough on the way in, did you really earn the title?

Photography was once seen as mechanical theft rather than art.  Sampling was attacked as stealing.  Scratching records was treated as vandalism.  Synths were dismissed as fake instruments.  Drum machines were accused of killing feel.  Comics were treated as disposable junk.  Film itself was once thought of as low entertainment.

Every generation, it seems, finds a way to accuse the next one of fraud.

Stephen Fry has often made the point that, as someone who loves the English language, people expect him to stand against slang.  But he finds slang fascinating, because it is language doing what language has always done: adapting, shifting, inventing, finding new ways to make meaning.  Slang is not the sad little byproduct of language.  It is one of its defining signs of life.  Art is often much the same.  The people who care most about it are often asked to police its boundaries, when what they may actually be seeing is the medium changing in the hands of a new generation.

And often what sits beneath the accusation is not just concern for standards, though sometimes that is part of it.  It’s also anxiety about access.

Because new tools tend to do one deeply offensive thing: they let new people in.

I’ve watched so many panels talking about the next generation of creators and how much we need them.  Because, until humanity fixes the final bug of illness, ageing and death, the future of our industries literally depends on them.  But every time they try to come in through a side door, we tell them they’re doing it wrong.

Many young people, stripped of the opportunities many of us took for granted don’t know what the “right” way is… and isn’t that kind of our fault?  We’re masters of media, yet we’re completely incapable of doing what creators do… tell our own stories and amplify ourselves through a more social type of media.

These people, both young and old, are just picking up whatever opportunity is in front of them and they’re starting to make things at a velocity we can only dream of.

They are often clumsy at first.  Mostly derivative.  Sometimes embarrassing.  But creativity is a muscle and reps count…. So, not now, but maybe soon; they might just be brilliant.

And that’s how culture moves.  Always has.

Modern music producers don’t need to book a studio and hire an orchestra to make something lush and ambitious.  They can have an orchestra at their fingertips. They don’t have to pay session musicians unless they want to.  Most often, they don’t.

Are they artists?

Of course some are hacks.  Of course some are formula merchants.  Of course some are replacing craft with convenience.

But some are artists.

The presence of a new tool doesn’t settle the question.  It never has.

What makes the AI moment harder is that the ethical complaint is, mostly, correct.  This is not just another story about conservative critics sneering at innovation.  The training issue is real.  The consent issue is real.  The compensation issue is real.  The provenance issue is real.

So this is not an argument for naive equivalence.  AI is not simply the same as the synthesizer, the camera, or the sampler.  The moral circumstances are messier than that.

But even with that acknowledged, it is still a mistake to flatten everyone on the user side into one moral category.

There’s a difference between the companies that trained these systems on other people’s work without permission, the executives using them to cut labor costs, the mediocre opportunists using them to cosplay as makers, and the kid in a small town who loves images or stories or films and is using the first tool that has ever made participation feel possible.

Those are not the same person.

And if we are serious about art, we should be careful not to turn “protecting artists” into “protecting the exclusivity of being allowed to try.”

Because not everyone starts with access.  Not everyone starts with craft.  Not everyone starts with money.  Not everyone starts with permission.

Some people start with longing.

And longing has always made fools of people before it makes artists of them.

So yes, defend artists.  Absolutely.  Demand the 3 C’s: credit, compensation, and consent.  Draw hard ethical lines around exploitation.  Push back on the use of these tools as a blunt instrument for cost savings or cultural deskilling.

But don’t make the mistake of assuming that everyone who reaches for a new creative tool is contemptible.

Some of them are just people who want in.

And culture has always advanced because some of those people kept going.

After reading Doug Shapiro (Season 2 Podcast Guest) on the next disruption of media…

(Honestly, you can read the below, or you can watch Doug’s keynote below…  your choice.  But most of what i’m saying, he says in 30 min…  Are you a fast reader?)

Doug Shapiro has been giving a wonderful Keynote speech for the last year or two and it keeps getting better… its latest iteration he’s just given at the Academy of Television Arts and Sciences has a paper and presentation circulating on generative AI and media that are well worth your time.

(Please follow links at the end of this article)

Doug has done something very useful. He has taken a subject that is usually discussed either in the language of hype or fear and returned it to structure. He’s put generative AI back inside the longer history of media. Once you do that, you realize that the AI conversation is just the next turn of a wheel that has already been spinning for quite some time.

His central thesis is elegant and, I think, right.

The first great disruption of media was distribution. The next great disruption of media is creation.

It’s clean and clarifying. More to the point, it allows you to see why this moment feels so potent. Generative AI is not arriving into a settled media market. It is arriving into one already transformed, already loosened at the joints, already living with the consequences of the previous great upheaval.

The first great disruption was distribution

It is easy to forget how separate the old media world used to be. Records belonged to one system. Theaters to another. Newspapers to another. Broadcast television to another. Each had its own infrastructure, its own supply chain, its own economics, and its own keepers at the gate. The whole thing had the look of permanence because permanence is the schroud monopolies tend to wear.

Then digitization arrived and, with it, bits. A universal symbolic language for text, image, video, and audio. Once that happened, media could live in any system all at once. Media moved from siloed to unified, from one-way to two-way, from local to global, from physical infrastructure to virtual infrastructure. Then the economics followed. Scarce and expensive became abundant and cheap.

That was the internet’s great act upon media. It lowered the cost of moving bits. It made distribution vastly easier, vastly broader, and vastly cheaper. If you want to understand most of the turbulence of the last twenty years, that is the place to begin.

We are still living in the consequences of that first shift

One of the best lines in Doug’s deck is that most of the turbulence and displacement in media today is a lagging indicator of the last disruption. It explains the strange atmosphere of the business so well. For years now, media has carried that faint electric feeling of a house being renovated while everyone is still trying to hold dinner in the dining room.

Doug organizes the current state of media under six headings: stagnation, disintermediation, fragmentation, deflation, globalization, and concentration. That list reads  like the recent minutes from every boardroom and agency offsite in the business.

Time spent with media has largely flattened. Growth becomes a fight for share. Middlemen are removed, then rebuilt in new guises. Audiences splinter into finer and finer pieces. Prices soften under the weight of expanded supply. Competition becomes global as a matter of course. Power concentrates upward even as participation broadens outward. It is quite the trick.

The creator side of this story matters enormously. Independents upload oceans of music. YouTube swallows Hollywood whole in terms of volume. Social video takes an ever larger slice of viewing. Mobile rewrites gaming. The creator media economy grows into a material share of the total market and, more importantly, a very material share of the growth. Supply, once kept in relatively dignified check by budgets, crew sizes, formats, and geography, begins to pour.

And as supply pours, attention gets more brutally concentrated. In the traditional distribution system, something like 10 percent of content accounts for 80 percent of viewing. In creator media, the curve gets dramatically steeper. It is closer to 1 percent accounting for 99 percent of the viewership.

That is an astonishing compression of outcomes. The head gets smaller, the tail gets longer, the middle gets thinner, and the economics become much more hit-driven.

That statistic helps explain why creator markets can feel both abundant and ruthless at the same time. There is more participation, more output, more access, and more possibility. There is also a fiercer concentration of attention. The prize pool gets larger, the field gets more crowded, and the winners take a disproportionate share of the day.

At the same time, audiences change. Their definition of quality changes. The old markers remain, of course. Famous actors still count. Big budgets still count. Production values still count. Prestige still counts. Brand names still count. Yet the center of gravity moves outward. Authenticity matters. Relatability matters. “Relevance to me” matters. Ease of finding matters. Digestibility matters. Social currency matters. A thing’s ability to travel through a group chat or a feed or a fandom starts to matter every bit as much as the money you can see on screen.

Doug’s framing around platforms is also very good. Traditional media is reflective. Social media is reflexive. Platforms have built enormously powerful systems around our biology: variable rewards, novelty, feedback loops, personalization, autoplay, infinite scroll, and the removal of stopping cues. That is not merely a cultural detail. It is one of the structural explanations for where attention went, why it stayed there, and why so much of media has spent the last decade learning to live on new terms.

All of that is the context for generative AI. And it matters. The next disruption is entering a market already reworked by the last one.

The next disruption is creation

This is where Doug’s argument becomes more than just neat. It becomes genuinely useful.

If digitization introduced a universal way to represent anything, his case is that generative AI introduces a universal way to create anything. In his deck, this appears as a second symbolic layer. The first layer eroded barriers in distribution. The next one erodes barriers in creation itself. Time, modality, state, and provenance all begin to loosen.

That has a very particular texture.

• Human-constrained becomes machine-scaled.
• Time-constrained becomes real-time.
• Single modality becomes multimodal.
• Discrete provenance becomes fluid provenance.
• Finished state becomes fluid state.

Then the economics change again.

Scarce and expensive becomes abundant and cheap.

Doug places the internet and generative AI side by side in one of the strongest slides in the deck. The internet collapsed the cost to move bits. GenAI may collapse the cost to make bits.

It is one of those sentences that enters the mind quietly and then starts rearranging the furniture.

Because that is a much deeper change than most current conversations about AI allow. This is not about faster workflows or cheaper asset production or amusing tools that can make a storyboard in thirty seconds. It is about creation itself beginning to behave like an abundant input.

That changes everything downstream.

Why this one may move faster

There is a temptation, especially among people in established industries, to imagine that every great shift must unfold with the stately rhythm of the previous one. Doug is persuasive on why this one may move more quickly.

First, there is the matter of scale. Hollywood produces roughly 15,000 hours of content per year. YouTube sees something like 300 million hours uploaded annually. Internet-scale volume has already arrived. If even a microscopic percentage of that begins to compete on a level audiences find viable, the implications are obvious. A little quality in a great sea of quantity goes a surprisingly long way.

Second, there is the compression of production economics. Doug’s comparison between Inside Out 2 and Where the Robots Grow (Directed by Tom Paton, a Season two guest on our Podcast) is useful precisely because it is not really about artistic equivalence. It is about ratios. Four to five years versus three months. A cast and crew of 708 versus 9. $200 million versus $700,000. The point is not that one replaces the other wholesale. The point is that cost, time, and labor are compressing with astonishing force. A very high percentage reduction in those categories produces a market event all by itself.

Third, the conditions for adoption are already in place. Broadband is here. Streaming is here. Global platforms are here. Creator behavior is here. Algorithmic distribution is here. Consumers already live inside personalized feeds and increasingly fluid definitions of quality. YouTube already sits in the living room. This transformation does not have to wait for the road to be built. The road is full of traffic already.

New media starts by imitating the old one

This is another part of Doug’s framework I like. New media tends to begin skeuomorphically. It borrows the shape of what came before. Film begins looking suspiciously like recorded theater. Online publishing begins as static documents. Online video begins close to television. Then, in time, the medium discovers its own manners and starts behaving like itself.

Generative video is likely to do the same.

The first wave will look like cheaper versions of familiar things. More affordable films. More affordable television. Lower-cost advertising. Accelerated pre-production. Quicker iterations of established formats.

Fair enough. That is how new media announces itself. Yet the more interesting future lies in the forms that belong natively to the medium. Doug lists some of them plainly: fan creation and remixes, interactive experiences, personalized media, emergent forms, multimodal storytelling, and 3D or spatial experiences.

Cheap and fast.

Real-time.

Multimodal.

Unconstrained by physics.

Spatial.

That is a very different sort of media object than a fixed film or advertisement or article. It is closer to a system. Something living, responsive, participatory, and perhaps a little unruly.

What is already visible

Doug is sensible about uncertainty. He names the open questions clearly: realism, labor, control, consumer acceptance, native formats, legal settlement. Those questions will shape the slope and contour of adoption. They are, in other words, the weather.

The climate is easier to see.

• Production costs compress across the entire curve.
• Supply expands toward something like infinity.
• Pricing comes under pressure.
• AI intermediaries become more common.
• Consumer definitions of quality continue to widen.
• More fluid media forms become viable.

He also includes a few choice pieces of evidence from the present. AI-written articles have risen dramatically since the arrival of ChatGPT. AI video, a medium that only a short while ago seemed chiefly useful for generating nightmares and accidental comedy, is improving at a comical speed. The progression from the grotesque spaghetti-eating clips to outputs with real cinematic coherence has happened quickly enough to make one a little cautious about declaring what will remain impossible.

There is also the reminder that audience preferences have already been drifting away from high production values as the singular north star. That work was done by the last disruption. GenAI simply enters a world where that evolution has already been underway.

The question beneath the whole thing

Doug eventually arrives at the question that sits underneath the rest of the deck:

What becomes more valuable when content is functionally free?

That is the right question because it shifts attention away from the content object and toward the wider system in which it lives. When an input becomes abundant, the product built from it tends to lose some of its old aura. Value then moves toward what remains scarce.

Doug frames this through the 4Cs: challengers, consumers, complements, and chokepoints.

That pattern has repeated itself often enough to be trustworthy. An input becomes abundant. The core product starts to resemble a commodity. Value gathers around scarce complements and around the places in the value chain where control can be exercised.

His examples from agriculture, photography, broadband, and enterprise software are very good. Cheapness does not make value disappear. It relocates it.

In the world of generative media, the complements are already beginning to show themselves. Recommendation agents. Authenticity and verification. Fraud and brand safety. Creator financing. Marketing services and analytics. Brand extension services. Real-world events and access. Identity and status. Exclusive content and merch. Fan creation and participation. Personalization and customization. AI training rights. Summarization and highlights agents. Cultural localization. Proof of provenance. Curation as a service. Rights clearance at scale.

That list is exciting because it suggests an economy springing up around the new abundance.

Chokepoints are where the strategy is

Doug’s distinction between complements and chokepoints is especially valuable. Complements are where value is created. Chokepoints are where value is captured.

That difference can save a great deal of muddled thinking.

His list of emerging chokepoints is excellent: measurement and analytics, professional validation and infrastructure, monetization, fame and following, human provenance, agents, trust and authenticity, marketing, first-party data, curation, distribution, community, systems integration, brands, and IP.

Then he goes a step further and breaks down the natural owners of different chokepoints. Platforms tend naturally toward distribution, curation, first-party data, monetization, and agents. Creators tend naturally toward trust and authenticity, curation, human provenance, fame and following, and community. Incumbents tend naturally toward trust and authenticity too, along with IP, brands, community, marketing, and professional validation infrastructure.

This is where the deck stops being merely explanatory and becomes strategic. If content is cheaper, more abundant, and more fluid, then the real contest sits in owning the scarce layers around it. The trusted layer. The curatorial layer. The validating layer. The branded layer. The data layer. The agent layer. The relationship layer.

That is where much of the next decade’s value will be organized.

The bottom line

Doug’s last slide puts it simply: more competition, more complexity, new opportunities.

Quite.

The first great disruption of media changed how media was distributed. It gave us the market we are still living inside now: fragmented, global, creator-heavy, platform-shaped, price-pressured, and forever in some subtle state of rearrangement.

The next great disruption changes how media is made and, with that, what media can become.

That is why this moment feels so charged. One great change has not finished reverberating before the next one has begun to roll through. First the pipes were remade. Now the factory is being remade. First the cost of moving bits collapsed. Now the cost of making bits begins its descent. First media was unified in representation. Now it becomes more fluid in creation.

Doug’s work is valuable because it restores sequence to all this. It gives the present a lineage. It allows you to see that we are not staring at a random pile of technological novelty. We are standing in the next room of a house that has already been renovated once before.

That is a useful thing to remember, particularly when the wallpaper is still wet.

And I’ll say one other thing. Doug was a guest on the KoobrikLabs podcast, and he is exactly as lucid there as he is on the page. If this subject interests you, it is well worth hearing him talk it through.

His Substack is also one of those subscriptions that pays for itself almost immediately. This is the five dollars a month I am more than happy to pay. I basically quote Doug Shapiro once a day, which by my rough maths makes it something like sixteen cents a day for a very steady supply of clarity. That is a bargain.

In the last year, I’ve become a sort of creator and I’ve been interviewing creators and it’s made me realize something profound…

Advertising, for all its neuroses and committees and strategic throat-clearing, has something rather wonderful going for it: it is still, at heart, a makers’ business.

That is easy to forget beneath the decks, the procurement rituals, the risk mitigation, the disclaimers, the social-first ecosystems, and the sort of synthetic earnestness that now clings to modern marketing language like static.

But strip all that away and what remains is this: advertising is made by people who make things.  Writers.  Art directors.  Directors.  Editors.  Designers.  Production designers.  Cinematographers.  Stylists.  Animators.  VFX artists.  Grips.  Gaffers.  A small army of obsessives with difficult taste and highly specific skills, all trying to wrestle a bit of magic into existence before the client changes the supers.

And yet, bizarrely, the industry persists in treating the making of the work as if it were a state secret.

Everything is embargoed.  Everything is precious.  Everything is hidden until launch day, at which point the campaign is hurled into the world with the faintly desperate hope that people will not only notice it, but care.

And presuming people will care about advertising is a kind of madness.

Advertisers today have far more in common with creators than they do with Hollywood.  And I think this is a good thing.  Because creators, unlike Hollywood, have understood something enormously important: the story of creation is itself valuable media.

They build in public because they know that process does not diminish the thing.  It enlarges it.  It gives people something to root for.  It allows audiences to invest emotionally before the final object is even finished.  It creates anticipation, familiarity, affection, and trust.  It turns the work from an isolated drop into an unfolding event.

And in this regard, advertising is leaving a ludicrous amount of value on the table.

Agencies and brands should learn a lesson Hollywood still refuses to learn: show the making.  Show it early.  Show it while it is happening.

Not after the ad has aired, not tucked into some tasteful behind-the-scenes cut-down that appears a day later when the oxygen has already left the room, but in the weeks leading up to launch, while the thing still has momentum to gather and meaning to accumulate.

Because what, exactly, are we protecting?

The secret ending of the John Lewis Christmas ad?  The punchline of a beer spot?  The reveal of a delightful visual trick for a cereal brand?  Please.  We are not safeguarding the nuclear codes.  We are selling soup, trainers, and mobile contracts.  The public is not sitting there trembling with concern that the emotional arc of a holiday commercial might be spoiled in advance.

Indeed, even modern film marketing has become so deranged in its willingness to give away entire plots in trailers that I’ve stopped watching them altogether…. I sit listening to music with my eyes down until the movie starts.  I love movies so much, I have to protect myself from their creators who seem utterly committed to ruining them for me!

It makes advertising’s paranoia all the more absurd.

If film people wish to remain addicted to secrecy, one can at least understand the lineage of it.  Cinema was built in the age of scarcity.  The logic was simple: protect the release, protect the mystique, protect the asset.  That logic has become less convincing with each passing year, but one can see where it came from.

Advertising, however, doesn’t have that excuse.

Advertising exists in the open air.  It competes not with rival campaigns alone, but with the entire culture.  It is interrupted by memes, devoured by feeds, and judged against the standards of a world in which everyone from a teenage furniture flipper to a one-man design studio has already learned to narrate the making of their work better than most global brands.

The creator economy has demonstrated, beyond any reasonable dispute, that people love watching something come into being.  And they don’t care if it’s poorly filmed… in fact, that’s a feature not a bug.

They love seeing a thing before it is perfect.  They love becoming attached to the people making it.  Above all, they love feeling included in a special little club.

And that feeling, the glorious human satisfaction of being brought into the process, is not some side issue.  It’s media value.

Massive media value!

Am I speaking brand language yet?

Impressions, yes, if we must use the dead language of the industry.  But more than that: attachment.  Affection, anticipation, cultural texture.  A sense that the work matters before it arrives.  A sense, even, that one has a stake in it.

Imagine a costume stylist like Mr Gammon developing a devoted audience of his own because people simply cannot get enough of his taste, his eye, his running commentary… meow.  Imagine an agency creative team, creating an audience that is already primed for a brand launch because they have watched the thing develop in real time.  One could happily listen to Ed Wild tell cinematography war stories for hours.  I once got to watch Rich Orrick edit in real time and I was transfixed.  Let alone the opportunity to listen to Charlie Crompton tell a story… even the joy of wishing he’d end it could become meme worthy!  And Daniel Bergman?  Frankly, it is astonishing there is not already a camera on him twenty-four hours a day.  And lets remember Ringan…. If there ever was a face that had no business behind a camera… he would have been a star by now…  This is the point: the talent is there.  The fascination is there.  The audience is there.  The industry is simply failing to turn the camera around.

Remember when I said it was an absurdity that people would care about advertising… I’m not suggesting they would with this change.  I’m suggesting they would care about the people of advertising doing hard work well.

This is not some utopian fantasy.  It is simply the application of creator logic to an industry still behaving as though it is 1997 and mystery and spectacle alone can carry the day.

And there is, of course, another reason this matters now, one rather larger than media efficiency or launch strategy.

AI.

Our industry spends a great deal of time talking about AI, usually in one of two ghastly registers: either the breathless gospel of efficiency, or the hand-wringing lament about slop.  But if one steps back from the noise, one thing becomes rather obvious.  In an age when synthetic output is cheap, abundant, and increasingly plausible, the most valuable thing creative industries can do is demonstrate the reality of craft.

Not merely assert it.  Demonstrate it.

Show the choices.  Show the iterations.  Show the labor.  Show the taste.  Show the dead ends.  Show the absurd amount of expertise required to make something look effortless.

Because creators have already stumbled upon one of the best antidotes to slop: they let people see the work being worked on.

That is what gives it provenance.  That is what gives it texture.  That is what gives it human legitimacy.

The next generation has grown up in a media environment so thick with manipulation, performance, polish, and now machine-generated plausibility that authenticity can no longer be assumed.  It has to be evidenced.  Not solemnly proclaimed in a manifesto, but evidenced in the grain of the process itself.

And process, crucially, is not the enemy of magic.

This is the great misunderstanding of old media institutions.  They imagine that to reveal process is to diminish wonder, when in fact the opposite is true.  Showing what it takes to make a thing often increases the audience’s awe.   A beautifully built set is more impressive when one understands that somebody dreamt it, drafted it, fought for it, and then stood under impossible time pressure trying to get the paint right before dawn.

The making, especially in an age of cheap artifice, consecrates the work.

And yet here is the truly maddening part.  Everyone in advertising is forever lamenting the decline of craft.  Craft is not respected.  Craft is under pressure.  Craft is being flattened.  Craft is dying.

Fine.  Perhaps.

But here is the slightly embarrassing question: in an industry supposedly populated by the most media-literate people on earth, why is nobody making the media that might actually help save it?

Social media is sitting right there!

And what does the internet spend its time watching?  Craft!  Constantly.  Happily.  Obsessively.

I watched a man cut a lawn for fifteen minutes the other day.  Riveting.  A craftsman, plainly.  Then a woman cleaning a rug so filthy it looked medically concerning, and I watched that too.  Ten minutes gone.  Spellbound.  The algorithm, in its crude and often depressing way, has figured something out that much of advertising still refuses to admit: people are deeply drawn to watching skilled human beings do things well.

They like the process.  They like the transformation.  They like the judgment, the rhythm, the little decisions, the evidence of care.

In other words, they like craft.

So why, exactly, are we behaving as though our own industry is exempt from this?  Why do we insist on discussing craft solemnly on panels, over cocktails, and in green rooms, while refusing to use the most obvious medium imaginable to make craft visible, legible, and culturally magnetic?

It is a peculiar form of professional self-sabotage.

We say craft is dying, then hide the craftspeople.
We say the public no longer values the work, then refuse to show them the work being worked on.
We say the machines are coming, then decline to demonstrate the very human brilliance those machines are threatening to flatten.

Meanwhile, a generation of creators, many of them young enough to make the rest of us feel our joints ache, are building audiences by doing precisely what we will not: turning process into media, skill into story, and craft into something people can follow, share, and care about.

So yes, it does boggle the mind.

We are being outflanked not because craft has lost its value, but because others have become far better at making that value visible.

And while we are busy whining to one another about the death of standards, the kids are out there making the media that is eating our lunch.

Which is why the notion of the making-of video is both promising and, in its usual form, hopelessly timid.  Vix Jagger at Droga5 makes the case that we are moving into the age of the making-of video.  She is absolutely right!  But the industry’s current instinct is to make such material, wrap it in embargo tape, and release it after the campaign has already had its moment.  At which point it becomes less a cultural accelerant than a polite appendix.

What on earth is the point of that?

If the making is valuable media, then its value is greatest before and during the launch, not after the room has emptied.  Show the sketches in the lead-up.  Show the production design tests.  Show the camera rigs.  Show the agency creatives wrestling with the idea.  Show the comedy of it, the jeopardy of it, the absurd humanity of it.  Let people feel the work gathering.

Think of the impressions, yes.  Think of the earned media, absolutely.  But more importantly, think of the feeling.

Think of an audience that no longer sees an ad as a unit of branded communication, but as the culmination of a little drama they have already been enjoying.  Think of people who want to see the finished spot because they have become fond of the people who made it.  Think of what that does not only for campaign performance, but for the perceived value of the craft itself.

Because this is the deeper point.

When industries hide process, they accidentally train audiences to value only output.

And if audiences are trained to value only output, then output becomes easier to replace.

That is the genuine danger in the age of AI.  Not simply that machines will make things.  It is that humans will have done such a poor job of explaining what human craft actually consists of that the public will be invited to assume it was never all that meaningful in the first place.

Advertising has a chance to do better.

It can show people that craft is not decorative.  That taste is not interchangeable.  That great work emerges from collaboration, intuition, leadership, obsession, failure, adjustment, timing, memory, and instinct.  That the difference between something disposable and something unforgettable is often hidden in a hundred tiny human judgments made by people who have spent years becoming capable of making them.

And perhaps, in doing so, it can give a bit more public glory to the craftsmen and women who deserve it.

This should be their era.  They should be stars.  The production designers, costume designers, the editors, the agency teams, the art directors, the makers of peculiar brilliance.  They should not remain anonymous functionaries behind the curtain while the industry frets about the asset.  They are the asset.  They always have been.  But in an age of openness, we’re hiding them.

Show what it means for someone to become a head of department after years of honing their craft.  Show the wins.  Show the near-disasters.  Show the problem-solving.  Show the lives inside the work.

Bring people into those victories and you do something remarkable: you expand the love of advertising from a love of the finished ad to a love of the people who make it.

That is not indulgence.  That is strategy.

More to the point, it is common sense.

Hollywood, with its mausoleum instincts and velvet-rope secrecy, may continue to believe that concealment creates value.  But advertisers ought to know better.  We live in an age of abundance, not scarcity.  In an age of infinite content, the thing that cuts through is not just the finished piece, but the human trail behind it.

So… to the brands out there… for God’s sake: let the creatives post!  Let the production designers post.! Let the agency teams post!  Let the cinematographers, stylists, editors, and makers post before the ad launches!

Build in public.

Not because it is trendy.  Not because it is social-first.  Not because some innovation consultant with a lovely deck told you so.

Build in public because it is good for the work.
Build in public because it is good for craft.
Build in public because it is one of the best ways left to prove that people still made this.

And if you don’t do it for any of the good reasons I just listed above… do it just because you’re leaving masses of free, valuable media on the table!

You are sitting on a mountain of potential media value and behaving, for reasons no sane person can explain, as though it would be vulgar to use it.

The creators have already shown us the way.

When an agency opens its second office, post is where the cracks show first.

The creative team scales. The client list grows. But the infrastructure underneath – storage, render capacity, ingest discipline, archival policy was usually designed for a single physical location. So the second office gets a mirrored setup. More workstations. Another NAS. Another render box. Another set of permissions. Now you don’t have one system, you have two and they don’t quite behave the same.

That’s where friction creeps in, not because the machines aren’t powerful. But because they weren’t designed as shared infrastructure.

Start With Architecture, Not Gear

Let’s be specific about what a modern, scalable agency pipeline actually includes:

At the edge, you still need serious editorial hardware. Threadripper-class machines. 128–256GB RAM. Fast NVMe scratch. Calibrated displays. Quiet rooms. Editors should not feel latency.

But the workstation is no longer the system, it’s a node. Behind it sits a shared infrastructure layer:

On-prem still matters. High-speed networking inside the facility matters. Shared render capacity inside the facility matters.

But storage and compute orchestration cannot be purely local if you expect two cities to behave as one team, that’s the difference.

Why Cloud-Native Compute Matters

When I spoke with Darren O’Kelly at Untold Studios, he explained why they went cloud-native from day one. It wasn’t ideology. It was compute.

If you are doing serious motion, animation, finishing, or AI-assisted post, you will hit compute ceilings. A fixed on-prem render machine works – until three jobs hit at once.

Cloud-aligned infrastructure allows burst capacity.

You keep a powerful on-prem render node for predictable loads. But when you need additional GPU horsepower whether for heavy renders or AI workflows you scale outward rather than stall internally. That hybrid model – strong local infrastructure plus elastic cloud compute is the real evolution.

Pure on-prem caps you.

Pure cloud feels abstract.

Hybrid, designed properly, scales.

DAM Is Not Optional

Agencies often treat Digital Asset Management as something studios worry about. That’s a mistake.

Once you’re bi-coastal, ingestion discipline matters.

• Secure drive intake.
• Checksum validation.
• Structured upload into cloud storage.
• Consistent folder architecture.
• Metadata governance.
• Version control clarity.

Without this, cloud storage simply becomes a larger junk drawer.

A modern pipeline includes a defined ingestion protocol and asset lifecycle policy from day one. Not because it’s elegant – but because without it, scale breaks things.

Adobe vs Flame – Be Honest About It

You do not need to go full Flame in 2026 to build a serious agency pipeline.

Adobe’s ecosystem is strong. Premiere and After Effects cover the overwhelming majority of commercial workflows. Frame.io has normalized distributed review. Enterprise licensing now includes indemnity around generative AI usage, which is commercially meaningful.

For many agencies, Adobe and a properly designed infrastructure is entirely sufficient.

Flame makes sense if:

But understand what that means:

Flame isn’t just a software decision, it’s a staffing decision. Flame artists cost more, your hiring pool narrows, your overhead increases.

If you go Flame, go properly. If you don’t, Adobe is not a compromise anymore. It’s a mature professional stack — especially when protected under enterprise licensing.

Human Resource Reality

Here’s the part leadership teams usually want clarity on. How many people does this take?

If designed correctly, surprisingly few.

You need:

In a properly architected cloud-native environment, one competent infrastructure lead can oversee day-to-day operations. Monitoring storage tiers, scaling compute, managing licenses, maintaining security posture.

The key phrase is “properly architected.”

If you bolt cloud onto unmanaged local systems, one person cannot keep it coherent. If you design intentionally, you don’t need a data center team.

Storage Policy Must Live in the MSA

This is where agencies quietly lose money.

Your Master Services Agreements should state clearly:

• Active project storage remains in hot cloud tiers for six months post-delivery.
• During that six-month window, if clients require the project to remain active and accessible, they are responsible for associated cloud storage costs.
• After six months, the agency may archive the project to cold storage.
• If the client requires ongoing active access beyond that period, storage fees are passed through directly.

This isn’t aggressive. It’s responsible.

Cloud storage is recurring, agencies that absorb indefinite storage costs erode margin invisibly. Write the policy early. Enforce it consistently.

What Scaling Actually Changes

When designed properly, a bi-coastal pipeline includes:

Notice what it doesn’t include:

A Practical Conversation

At KoobrikLabs, we design hybrid cloud-native post infrastructures for agencies expanding across offices.

That means:

If you’re opening a second office, considering Flame, formalizing AI governance, or realizing your storage costs are quietly compounding, it’s worth stepping back and evaluating the architecture. Not to replace everything.

But to ensure you’re scaling one system – not multiplying two. Because once you’re bi-coastal, post isn’t a room it’s infrastructure.

And infrastructure should be designed, not accumulated

Somewhere between the third espresso and the fifth AI demo of the morning, a video began circulating by Chinese AI vision model Seedance: Tom Cruise and Brad Pitt, or at least digital approximations of them, bantering and fighting away in a synthetic clip that was convincing enough to make you blink, squint, and check the caption twice.

It was, depending on your perspective, amusing, impressive, or faintly chilling. But what it really was, more than anything else, was instructive.

Because that video is not about two movie stars. It’s about the future of ownership itself.

We have wandered into a moment where the most powerful technology companies on earth are arguing, in court and in public, that they should be allowed to ingest the entire creative output of humanity – films, books, scripts, songs, designs, photographs without permission or payment, on the grounds that it is “fair use.”

Their argument, stripped of the glossy demo reels and optimistic keynote slides, is quite simple:

We shouldn’t have to pay creators or patent owners, because our technology is going to benefit society as a whole.

It is an argument that sounds oddly familiar.

Historically, one of the central claims of communist ideology was that private ownership, especially of the means of production should give way to collective benefit. Individual creators, inventors, or owners should not stand in the way of progress that serves everyone.

In other words:
The collective good outweighs individual property rights.

And here we are, in the heart of Silicon Valley, listening to some of the most aggressively capitalist companies in history make a strikingly similar case:
Don’t worry about the individual creator.
Don’t worry about the patent holder.
Don’t worry about the rights owner.
The technology will benefit everyone. Therefore, the property can be used.

It is a curious ideological pivot, rabid capitalists suddenly making arguments that sound suspiciously like collectivist theory provided, of course, that the collective benefit flows through their balance sheets.

One imagines a burglar politely explaining that he hasn’t stolen the silverware at all; he’s merely redistributed it for the good of the neighborhood.

And yet, this is precisely the case being made.

The Foundation Everyone Forgets

The Western economy, if one may still use that phrase without being accused of nostalgia rests on a deceptively simple idea: that intellectual property is real property.

Not metaphorically. Not symbolically. Legally.

If you write a book, you own it.
If you design a drug, you patent it.
If you create a character, you license it.
If you invent a device, you protect it.

This is not a footnote in the system. It is the system.

Entire industries exist because of it:

Take away the enforceability of intellectual property, and you don’t just disrupt Hollywood. You destabilize the very mechanism that makes innovation economically viable.

No patents, no incentive to invent.
No copyrights, no incentive to create.
No trademarks, no incentive to build brands.

There’s more at stake than just Hollywood.

It is the quiet engine beneath modern prosperity.

The AI Exception That Swallows the Rule

Now comes the AI industry, asking for a rather special exemption—and, one might note, a rather communist idea, if I may plant a thought that will pay off later.

Their position, broadly speaking, is this:

“We need all of your data, your scripts, your films, your art, your code, your photographs, your books, your voice, your face so that we can build the future. And we should not have to pay for it.”

It is, in effect, a request to suspend intellectual property law for the most valuable dataset ever assembled: human creativity itself.

If they win that argument, the precedent will not stop at Hollywood. It will not politely confine itself to actors’ likenesses or screenplays.

It will spread.
If it is acceptable to train on copyrighted films without permission, why not:

The logic is the same. The principle is identical.
And once that principle erodes, it erodes everywhere.

A Global Ideological Contest

There is another layer to this, one that rarely gets discussed in polite tech panels.

The modern system of intellectual property is not universal. It is ideological.

The United States, the United Kingdom, and most Western economies are built on the assumption that individuals and companies have enforceable ownership over their creations.

China, by contrast, is governed by a Communist Party whose ideological roots do not center private ownership in the same way. Historically, state or collective interests have taken precedence when they conflict with individual or corporate IP claims.

For decades, Western companies have complained about:

From a Western legal perspective, this is IP theft.
From a different ideological perspective, it is industrial policy.

So when global norms around intellectual property weaken—when the world begins to accept that creative work can be freely absorbed into machines without permission, it does not occur in a vacuum.

It shifts the balance of power.
If Hollywood’s rights are diluted, so are:

And suddenly, the ability to manufacture a character toy without paying Disney or to produce a patented device and sell it under a different name becomes easier to justify, both legally and politically.

This is more than a technology debate… It is a geopolitical one.

Strange Bedfellows: Silicon Valley and the State

Here is where the plot thickens, in the way all good geopolitical dramas do.

On paper, American tech companies and the Chinese state occupy opposite ends of the ideological spectrum.

In practice, on this one issue, their incentives align.
Both benefit from a world in which:

Because the less ownership exists, the more data can be consumed.

It is the rare moment in history where trillion-dollar corporations and state-directed industrial strategies are, if not allies, then at least rowing in the same direction.

And in the middle of this current sits the creative industries: film, television, advertising, publishing, music wondering whether the concept of ownership still applies to their work.

Hollywood Is Just the First Battlefield

The Tom Cruise and Brad Pitt deepfake is not the end of the story. It is the opening scene.

If two of the most recognizable faces on earth can be convincingly simulated without consent, what does that say about:

Or, for that matter:

Once the principle is broken, it is broken for everyone.

What You Can Actually Do

For too long, weve been treating this like a philosophical debate, but it needs to be a legislative one.

The future of intellectual property in the AI era will be shaped not just in courts, but in parliaments and congresses.

If you work in a creative, technological, or knowledge-based industry, you have a stake in this outcome.

And the simplest, most effective thing you can do is write to your elected representative and make one point clear:

Intellectual property protections must come first – before the interests of AI companies.

Find Your Representative

A Letter You Can Copy, Paste, and Send

Subject: Protect Intellectual Property in the Age of AI

Dear [Representative/MP Name],
I am writing as a constituent and as someone who works in a creative, technological, or knowledge-based field.
As artificial intelligence systems rapidly advance, many technology companies are arguing that they should be allowed to train their models on copyrighted and patented material without permission or compensation, under the theory of “fair use.”
This is not just a dispute between AI companies and the entertainment industry. It is a fundamental question about the future of intellectual property itself.
The modern economy depends on enforceable IP rights. These protections underpin:

• Film, television, and music
• Software and digital services
• Pharmaceuticals and medical research
• Consumer electronics and industrial design
• Publishing, advertising, and fashion

If AI companies are allowed to absorb copyrighted and patented works without permission, it will weaken the legal and economic foundations of all of these industries.
I urge you to support legislation and regulatory frameworks that:

1. Require AI companies to obtain permission before training on copyrighted or patented material.
2. Ensure that creators and rights holders are fairly compensated.
3. Preserve the principle that intellectual property is real, enforceable property.

Protecting IP is not about resisting technology. It is about ensuring that innovation and creativity remain economically viable in the AI era.
Thank you for your time and for your service.
Sincerely,
[Your Name]
[City/Zip Code]

The Tom Cruise Brad Pitt deepfake may be a curiosity today.

But the question it raises who owns any intellectual property  in the age of machines is one of the defining economic and cultural questions of our time.

Last week, KoobrikLabs CEO and Head of Business Development, Orlando Wood and Rachel Duggan, spent a day at Artist and The Machine’s AI & Creativity Summit in Los Angeles. We went in expecting a pulse check on tools and trends. We left with something more valuable: a sharper sense of the creative responsibilities that come with this moment. 

The summit was a room full of people trying to answer the same question from different angles: what does meaningful creativity look like when generation is cheap, fast, and everywhere? 

Below are the threads we’re still unpacking and why they matter for the worlds we’re building at KoobrikLabs. 

1) Infinite output is pushing culture toward meaning 

When generative media becomes abundant, attention stops being the scarce resource – meaning does. Across the day, there was a shared intuition that audiences won’t reward volume for long. As production quality gets democratized, people will gravitate toward work with intention, emotional resonance, and point of view. 

That theme surfaced most clearly in Matt Zien’s conversation with Grimes. What stuck with us wasn’t a specific “AI workflow,” but the framing: if anyone can generate high-production content on demand, then the creative frontier shifts from novelty to significance. The differentiator isn’t “can you make something impressive?” It’s “did you change how someone feels or sees?” 

The future isn’t a bigger flood of content. It’s better reasons to care. 

2) AI can erase authorship – unless we defend it 

Our stance at KoobrikLabs is still AI can absolutely blur or erase authorship if it’s adopted carelessly – especially when tools are trained on unconsented work or when creators lose control over how their style, IP, or data gets used downstream. 

Hannah Elsakr’s session on maintaining artistic POV in an AI era put language to the tension we’re seeing across clients: AI can scale personalization and world-building, but without a strong creative center it also pushes toward sameness. The more the tools compress the technical gap, the more important it becomes to protect the artist’s (or studio’s) worldview – because that’s what can get diluted fastest. 

So the question isn’t “are we using AI?” 

It’s: What stays human, what gets assisted, and what should never be automated in the first place? 

This maps directly to why KoobrikLabs exists: creative teams need AI built around their point of view and rights, not the defaults of off-the-shelf platforms. 

3) We’re entering an era where AI values matter as much as AI literacy 

One of the most grounding moments for us was hearing Grimes talk about the moral and ethical philosophy of using these tools. The industry is holding two truths at once: 

Not “AI or no AI,” but which parts we choose to support with AI – and which parts we refuse to replace. 

That line will vary by project and medium, and that’s exactly why values matter. The next era won’t be defined by whether AI was used – it will be defined by how and why it was used. 

Our takeaway: AI literacy isn’t enough. We need AI values – and creative leaders have to help define them. 

What this means for KoobrikLabs 

While the summit centered possibility, our stance remains clear-eyed: today’s AI ecosystem isn’t safe by default for data or for authorship. Most off-the-shelf tools still create real risk of IP leakage and creative dilution, because they don’t give studios strong control over what gets trained, what gets retained, and how outputs are governed.  

So for us, the path forward isn’t opting out. It’s adopting AI inside guardrails that actively defend ownership, creative identity, and trust.  

That’s the heart of our model: 

• Strategy: helping creative companies assess workflows and AI readiness, then translating that into a roadmap that fits their reality. 
• Support: managing the IT foundation and security posture so teams can adopt AI without exposing their data or creative identity. 
• Build: engineering bespoke AI tools that automate the repetitive, protect the valuable, and amplify the uniquely human parts of making – with AI operating inside secure first-party environments, not open public systems.  

A lot of summit conversations circled the same practical problem we see every week: studios recognize AI’s potential, but struggle with safe adoption, integration, and internal trust. Our view is simple: your creative data and authorship are your future – and AI should only ever work for you, never against you.  

The industry doesn’t need more generic tools. It needs creative-native infrastructure: secure first-party data, structured intelligence, automation that empowers rather than replaces, and responsible innovation that defends rights while expanding possibility. 

If your team is navigating how to adopt AI safely and creatively, speak to KoobrikLabs about building secure, creative-native AI workflows.

In August, WPP stunned the industry with a 71% decline in ad revenue. For years, holding companies have relied on scale, data monopolies, and armies of strategists to stay ahead. That era is over.

The next generation of breakout agencies won’t lead with decks – they’ll lead with data.

For the first time, small and midsize agencies can access the same creative intelligence infrastructure that was once the sole domain of the big networks. The combination of language models, data clean rooms, and interoperable CDPs has eroded the old data moat. And the smartest independents are moving fast to seize the advantage.

The creative data paradigm shift

“Creative Data has never been on the table until language models were released. Creative Data is where financial data was in 1985 when people first realized computers were good with numbers. The same monumental paradigm shift is happening here… and grey areas are where art thrives.”
— Orlando Wood, CEO, KoobrikLabs

Language models don’t just tag content as “positive” or “negative.” They parse the nuance in billions of social posts, reviews, chats, and ratings.

Peer-reviewed studies show that models now excel at aspect-based sentiment analysis (ABSA) – identifying how people feel about different parts of a brand, product, or service within the same post (ACL Anthogoly; arXiv). Sarcasm detection, stance analysis, and intent modeling have also taken major steps forward

This turns what used to be marketing noise into actionable creative intelligence, in days rather than months.

The data moat has leaked

Big agencies no longer have a monopoly on data. Google’s reversal on third-party cookie deprecation has forced the industry to embrace a hybrid privacy model – legacy IDs + first-party data + clean rooms – standardized by IAB Tech Lab.

For independents, this is a once-in-a-generation opportunity. The infrastructure they can now rent and configure – CDPs, warehouses, clean rooms – was prohibitively expensive just a few years ago.

Meanwhile, holding companies are validating the direction with massive investments: Havas has committed €400M through 2027, and WPP is betting big on its “WPP Open” AI OS

But scale is no longer the determinant of insight velocity.

Early adopters that re-architect their workflows around AI are seeing 12–18% margin gains once reporting and creative cycles are integrated.

From polarity to precision

Classic social listening tools forced every post into positive / negative / neutral buckets. Not only is it not giving the full picture, to even get to that limited level of analysis required HUGE amounts of human input. LLMs break that trap. They can boil the oceans and structure the data and sentiment details around a creative output into actionable and analyzable data.

Imagine this tweet:

“I usually love Brand X, but this new product is a major misstep. I hope they get back to last year’s form.”

The creative implication? Message a “return to standards” and offer transparency to loyalists. Multiply that by millions of posts, and you get a creative analytics engine that feeds briefs and A/B tests every week

A 90-day plan to build a data-first shop

KoobrikLabs has distilled this into a pragmatic, three-month roadmap:

1. Days 0–7 – Stand up your warehouse & CDP, connect social/review/CRM data.
2. Days 8–30 – Ship your first LLM pipeline (entity/aspect extraction → sentiment →stance → emotion).
3. Days 31–60 – Wire insights into creative sprints, run 10–20 A/B/C tests.
4. Days 61–90 – Standardize briefs, reporting, QA, and model improvement loops

The future belongs to data-first creatives

This is about arming creativity with better intelligence. The agencies that win the next decadewill be the ones that treat creative data as seriously as media data—because the two are now intertwined.

If you’re a small agency, this is your moment. The tools are ready. The data is abundant. The incumbents are slow.

Get in touch with KoobrikLabs to start your 90-day data transformation.